1. Field of the Invention
The present invention relates generally to a computer-implemented image processing method, and more particularly to a computer-implemented image processing method for increasing a dynamic range of a gel electrophoresis image by combining a plurality of gel electrophoresis images into one composite gel electrophoresis image.
2. Description of the Background Art
Image processing is a method of manipulating an image or image data in order to enhance desired features or to diminish undesirable features. Image processing may enhance the usefulness of an image by changing the intensity, contrast, borders, size, placement, etc. of an image.
An image processing algorithm may be reduced to a set of steps that may be automatically and rapidly applied to an image, therefore dramatically streamlining image processing. This is of great importance in applications where large amounts of raw data must be reduced to meaningful results. Computers and digital electronics have brought about a multitude of ways in which images may be processed and manipulated. Numerous mathematical algorithms may be used, and image data may be processed on the level of individual pixels (in computer terms, a pixel is a basic picture element and is the smallest unit of visual information in an image).
One area in which computer-implemented image processing is useful is in the area of macromolecular analysis. Modern medicine has made great advances through the study of body chemistry and cell components. Living tissue is made up of a vast array of macromolecules, or large molecules, which perform a vast array of functions. Macromolecules, their identity, placement, and function, are important for many reasons, including, for example, drug actions and interactions, drug concentrations, body chemistry, DNA and RNA analysis, protein detection, protein generation, etc. Macromolecular analysis is particularly useful in stained gel applications, and may encompass applications such as, for example, protein analysis, DNA analysis, RNA analysis, etc. Large scale automation and computer processing are needed because of the huge numbers of component combinations that must be identified.
A macromolecular analysis has several general steps. First, a test sample is prepared, containing a test material to be analyzed. The prepared test sample is then electrophoresed to physically separate components of the test sample. Electrophoresis is a process wherein macromolecules suspended in a liquid or gel are subjected to an electrical field, physically separating particles on the basis of inherent electrical charges and/or size. The electrophoresis separation may be performed in one or more dimensions. A two-dimensional electrophoresis process creates a two-dimensional distribution of components throughout the electrophoresis gel. The electrophoresis is generally followed by a staining step wherein a stain is bonded to a certain type of molecule contained in the macromolecules of the test material. Typical stains include visible and fluorescent stains. In a two-dimensional electrophoresis gel this creates a two-dimensional pattern of components (spots).
As a step in the macromolecular analysis process, an image may be captured in preparation for the spot or pattern analysis. The pattern may then be analyzed to determine the macromolecular components, such as proteins, nucleic acids, polysaccharides, etc. Patterns may be analyzed in a variety of ways, including a comparison to a known pattern or set of components. The analysis of images or patterns as a step in macromolecule analysis requires that the images or patterns be well developed and complete in order that a final determination be reliable.
The relative positions or patterns of the spots can be used to determine the macromolecular components. The pattern analysis step is critical, because even if the process is carefully controlled up to this point, an incorrect pattern analysis may yield incorrect, confusing, or misleading results. This is because the size, physical location, and intensity of electrophoresed spots can be used to determine the macromolecular components of a sample under test.
Image development and analysis has typically worked with a single image, and spots or patterns of spots from this single image are analyzed. However, there is a drawback in using only a single image because it is difficult if not impossible to measure accurately intensities of both faint and intense spots from the same image. The ratio of the most measurable intense spot to the least intense measurable spot is called the dynamic range. A process that drops faint objects or that allows a dark or heavy object to obscure other objects is said to have a poor dynamic range.
There are three cases that need to be considered:
1. In macromolecular analysis methods where a carrier, such as a gel slab, is immersed in a developer or stain, individual spots may become visible at different rates, so that over a time span spots and patterns of spots may appear, darken, and ultimately reach saturation. There is no single point in time that yields optimal visualization for all objects in the image simultaneously. Taking multiple scans during development is required in order to maximize the information about both faint and intense objects.
2. For autoradiographic methods the sample is first tagged with radioisotopes. The carrier (gel slab) is placed against a) a photographic film, or b) a phosphorimaging plate for a period of time until the desired exposure is reached. For a), the film is developed and scanned to produce a digital image. For b) the plate is scanned in a specially designed laser scanner which also yields a digital image. For both cases the dynamic range is determined by the selected exposure time. There may be no exposure time value that is optimal for quantifying all objects in the image simultaneously. Multiple scans taken for different exposure times are required to capture information for both faint and intense objects.
3. For fluorescently-stained gels the gel is typically scanned using a CCD or other type of camera (suitably filtered to accept light at the emission wavelengths) while illuminating the gel with a light source operating at the proper excitation wavelengths. The dynamic range will be influenced by the combination of illumination and exposure settings. Again there may be no single combination of settings that is optimal for quantifying all objects in the image simultaneously. Faint objects will not be visible at short exposures and intense objects will be saturated at the longer exposures. Multiple scans with different exposure and/or illumination settings are required in order to maximize the obtainable information.
For all three cases above, multiple images are required in order to maximize the dynamic range and obtain quantitative information about both faint and intense objects. The analysis can take two forms:
1. Analyze each image separately and combine the results.
2. Combine the images and analyze the resultant combination image.
This invention addresses the latter case. That is, multiple images are combined to form a single image with greatly enhanced dynamic range, and that single image is used for both analysis and inspection.
A computer-implemented image processing method for increasing a dynamic range of a gel electrophoresis image by combining a plurality of gel electrophoresis images into one composite gel electrophoresis image is provided according to a first aspect of the invention. The computer-implemented image processing method comprises the steps of fitting gel electrophoresis pixel intensity values for a subject pixel to a mathematical function, computing from the mathematical function a pixel intensity value according to a predetermined rule, and inserting this pixel intensity value into the composite image.
A computer-implemented image improvement apparatus for increasing a dynamic range of a gel electrophoresis image by combining a plurality of gel electrophoresis images into one composite gel electrophoresis image is provided according to a second aspect of the invention. The computer-implemented image improvement apparatus comprises an image capturing device, and a computer having a memory and communicating with the image capturing device, the computer capable of receiving and storing into the memory a plurality of gel electrophoresis images from the image capturing device, the computer being further capable of fitting a plurality of intensity values of a pixel to a mathematical function over time and computing an optimal pixel intensity value for use in the composite image.